Applicants claim priority under 35 U.S.C. xc2xa7119 of GERMAN Application No. 199 04 347.7, filed: Feb. 3, 1999. Applicants also claim priority under 35 U.S.C. xc2xa7120 of PCT/DE00/00139, filed: Jan. 12, 2000. The international application under PCT article 21(2) was not published in English.
The invention relates to a method for processing a seismic 2-D or 3-D measurement data set comprising a great number of seismic traces each comprising a series of data points occupied by amplitude values.
Methods for exploring seismic data are employed worldwide for the purpose of obtaining additional knowledge about the spread of subterranean geological structures in addition to information gathered from sunk drilling holes. Owing to the information obtained from seismic data it is often possible to dispense with further cost-intensive exploration drilling operations, or to restrict their number to a minimum.
Sensors (geophones/hydrophones) are employed in the seismic exploration of subterranean structures that are lined up one after the other (2-D-seismology), or which are receiving sound waves. Such waves are excited by a seismic source, for example by an explosive charge, vibratory excitement or air guns, and are partly reflected back to the surface by the beds of the earth. The waves are registered by the sensors on the surface and recorded in the form of time series. Such a time series represents the seismic energy received in the form of amplitude variations. It is digitally stored and consists of uniformly arranged data points (samples), which are characterized by the time and the associated amplitude values. Such a time series is referred to also as a seismic trace. The measurement series migrates over the area to be explored, so that a seismic 2-D profile is recorded with such an arrangement.
The goal of the subsequent processing operation is to suppress the noise, for example by batch processing, or with the help of filters employed in a targeted manner. The results so obtained are vertical profiles in which amplitudes and propagation times as well as attributes derived from amplitudes are represented that serve as the basis for further geological evaluation. The geological strata can be observed on a profile by lining up the amplitudes laterally.
If the data are recorded not only along a line but in a flat matrix, a three-dimensional data volume is obtained. In the case of the 3-D volume, an amplitude value is assigned to any desired point in the underground structure that is described, for example by Cartesian coordinates. The vertical direction is measured in time (sound propagation time).
Large amounts of data (several gigabytes) are collected in such a process, which are stored and subjected to processing before the actual interpretation is possible with respect to, for example further exploration of the subterranean structures. Such processes require comprehensive computer resources and software for processing and correcting the received signals. The result is a seismic volume in the form of a 3-D data set that represents physical properties of the explored subterranean structure in a seismic reproduction.
Any desired sections such as, for example vertical profiles and horizontal slices relating to different depths of exploratory drilling can be extracted from said data set, which are then interpreted by geophysicists and geologists in the further course of the exploration operation. As such interpretation of the seismic reproductions so obtained substantially comprises an optical correlation, attempts have been made to automate such reproductions through subjective interpretation depending on one or a number of interpreters.
A method for seismic data processing is known from WO 96/18915, by which a seismic 3-D volume is divided in a great number of horizontal slices that are vertically standing one on top of the other and spaced from each other, whereby at least one slice is divided in a multitude of cells. In this process, each cell has at least 3 trace sections, whereby the first and the second trace sections are arranged in a vertical plane in the direction of the profile (inline), and the third trace section with the first trace section is arranged in a vertical plane substantially perpendicular to the direction of the profile (crossline). A cross correlation is subsequently carried out between each two trace sections in the two vertical planes, which results in inline- and crossline-values that are dependent upon the inclination of the beds of the earth. Combining such values in one cell results in a coherence value for the cell that is assigned to a data point of the cell. The end result in turn is a 3-D data volume from which any desired sections can be extracted and represented.
A method and a device for seismic data processing by means of coherency characteristics is known from EP 0 832 442 A1. In said process, a seismic volume is divided in horizontal slices in a manner similar to the method employed in the aforementioned published document, and said slices are in turn divided in cells. Said cells have the shape of cubes in the simplest case. Based on the at least two trace sections present in a cell, a correlation matrix is formed representing in each case the sum of the differences between the inner and the outer products of the set of values based on the trace sections. The quotient based on the highest inherent value of the matrix and the sum of all inherent values is then computed as the measure for the coherence. A 3-D volume consisting of coherence values is subsequently obtained in turn as the result.
Furthermore, EP 0 796 442 A1 relates to a method and a device for seismic data processing, by which a coherence method is carried out that is based on a semblance analysis. In a manner that is similar to the one employed in conjunction with the two aforementioned methods, a seismic data volume is divided in at least one horizontal time slice and the latter is then divided in a great number of three-dimensional analysis cells, whereby each cell comprises two predetermined lateral directions that are perpendicular in relation to one another, and at least five seismic trace sections that are arranged therein next to each other. A semblance value of the trace sections present in the cell is assigned to the corresponding data point in the respective cell. In said conjunction, the semblance is a known measure for the correspondence among seismic trace sections. By searching various earth bed inclinations and directions, the incidence and the direction of incidence of the analyzed reflector are then determined based on the best coherence. The computed inclination data are subsequently displayed for each cell in addition to the semblance value as well.
The three evaluation methods specified above do in fact permit supporting the data interpretation in an automated manner; however, the higher objectivity in the interpretation achieved in that way is traded for substantial expenditure required for computing the seismic data.
An image processing method is known from the presentation of the DGMK Deutsche Wissenschaftliche Gesellschaft fxc3xcr Erdxc3x6l, Erdgas und Kohle e.V. [German Scientific Society for Oil, Natural Gas and Coal], Tagungsbericht [Proceedings] 9601 (1996) by C. HELLMICH, H. TRAPPE and J. FERTIG, which is titled xe2x80x9cBildverarbeitung seismischer Attribute und Geostatistik im Oberkarbonxe2x80x9d [Image Processing of Seismic Attributes and Geostatistics in the Upper Carboniferous]. Said method permits a quantitative characterization of seismic representations and thus further interpretations of the lithology. Different image processing filters are employed in said process on amplitude charts, and the variations or the continuity of the local neighborhood are quantified. Said filters represent 2-D multi-trace filters, and the local environment surrounding a data point is evaluated with the help of such filters. Operators employed for said purpose include the entropy and the dispersion operators, among others. Charts can be produced for the interpretation with all attributes. The xe2x80x9centropyxe2x80x9d or xe2x80x9cdispersionxe2x80x9d quantities are in this conjunction dimensional figures that quantify the variations or continuities of the amplitude within the local environment.
Application of the aforementioned methods for large areas is frequently excluded for cost reasons.
U.S. Pat. No. 5,432,751 and U.S. Pat. No. 5,153,858 describe the assignment of the value xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d to a sample, whereby such allocation only serves the purpose of marking and quickly finding again points in the seismic signal showing a defined characteristic. In said process, the purpose of such markings is to combine said points at a later time in a semi-automated process in a geological horizon (automatic picking), whereby the reduction in memory locations achieved through such assignment permits interactive processing of the entirety of the characteristic points. Therefore, the set of measured seismic data is first compared based on a defined characteristic and then marked according to the result of the corresponding horizon by xe2x80x9c1xe2x80x9d. Said data set then exclusively serves for quickly finding again corresponding data positions of the original seismic data, which are substantially more comprehensive.
The problem of the invention is to propose a processing method for data sets of seismic measurements by which it is made possible to identify geological structures such as, for example faults or bed displacements, and also the stratigraphic, lithological and petrological conditions, with the lowest possible expenditure in terms of computing, paired at the same time with high objectivity of the results.
Said problem is solved with the method according to claims 1, 2 or 3.
It is essential to the invention in this conjunction that the set of measured data to be investigated, which data set comprises a great number of rows of data points occupied by amplitude values, such rows being time rows, as a rule, is converted into a binary data set, whereby a binary value xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d is assigned to each data point instead of the discrete amplitude value comprising several bytes. The discrete amplitude value is compared in this conjunction to a predetermined threshold value and assigned the number xe2x80x9c0xe2x80x9d if the amplitude value is lower versus the threshold value, or otherwise assigned the number xe2x80x9c1xe2x80x9d. The amplitude information thus is binarized. The amount of data is reduced by the factor 32, for example in connection with the usual amplitude resolution of 4 bytes.
The binary data set so generated is subsequently subjected to a similarity analysis in an environment defined by a predetermined cell size, where the semblance of the binary data present in the cell is analyzed for each data point and the associated central data point is assigned a quantity reflecting the semblance.
The computing time is reduced vis-a-vis comparable methods of interpretation by about 97% because the computation has to be carried out only with binary quantities. Furthermore, the data of the result require reduced memory locations versus comparable methods because 1 byte suffices for representing the attribute xe2x80x9csemblancexe2x80x9d, as a rule. Furthermore, due to the standardization of the binarization, the method is not depending on the level, so that no scaling problems occur with the representation of the result. Moreover, the result is more independent with respect to possible processing errors.
The data set generated as defined by the invention can be represented in the usual horizontal or vertical sections (slices and profiles), for example in gray levels or with color coding. Such charts and profiles show a clear reproduction of the geological structures such as, for example the localization of salt overhangs, the position and orientation of faults, bed and block displacements, horst and trench structures etc., and thus supply an instrument for assessing the underground. In particular, it is possible to determine on the basis of the data sets processed as defined by the invention hydrocarbon deposits, for example sites where oil and natural gas are trapped, and in general the lateral as well as also the vertical distribution of oil and natural gas deposits.
The value reflecting the similarity is computed by said method by counting the data points with the same binary value (xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d in each case) within the entire environmental cell, whereby the highest number is assigned to the central data point in the newly generated data set. High values reflect in this connection correspondence of the data values in the cell being viewed.
As an alternative, the determination of the similarity value is carried out by counting in each case the data points having the same binary value, xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d; however, separately for each horizontal slice of the cell having a data point. In an intermediate step, the greater number is assigned to the slice as the similarity value. According to said intermediate step, the sum of the individual values is assigned to the central data point in the newly generated data set. Horizontal weighting is taken into account with such a similarity analysis.
As a further alternative, weighting in the linear, vertical direction can be achieved along the respective seismic trace in that the data points having the same binary value, xe2x80x9c0xe2x80x9d or xe2x80x9c1xe2x80x9d in each case, are counted, but counted separately for each trace of the cell, i.e. for each binary time series of the latter. In an intermediate step, the greater number is then assigned to the trace as the similarity value. The sum of the individual, trace-related values of a cell is then assigned to the central data point in the newly generated data set.
As the usual amplitude values of seismic traces vary between +X and xe2x88x92X, whereby X is a maximally representable amplitude value, a threshold value around 0 would statistically supply an about equally weighed division of xe2x80x9c0xe2x80x9d and xe2x80x9c1xe2x80x9d in the binary data set generated in the binarization process. Preferably, however, a value is pre-adjusted that is by a few bits (LSB) greater or smaller than the threshold value.
Alternatively, it is possible to determine as the threshold value the amplitude value resulting prior to the binarization process as the most frequently occurring value from a histogram analysis of the set of measured data, or from a cutout therefrom.
If the cell approximated to the data point being processed comprises a rectangular/squared stone-shaped or elliptic/ellipsoidal environment, the result of the analysis will be obtained as much balanced as possible. Cube-shaped of spherically shaped cells are preferred in this connection.
A cell size that is suitable for many applications consists of 5xc3x975 data points in connection with a 2-D data set, or of 5xc3x975xc3x975 data points with a 3-D data set.
A statically and dynamically corrected, stacked and migrated seismic measurement data set is preferably used as the starting point. Further processed sets of measured data, for example additionally filtered and depth-converted data sets can be employed as well. Likewise, the application on unstacked data, for example single-shot combinations (shotgather) and CMP-gather is possible. This includes derived seismic attributes such as acoustic impedance (from the seismic inversion) and AVO-attributes (e.g. AVO-gradient, AVO-intercept) as well.